A munin network for the median nerve-a case study on loops
Applied Artificial Intelligence
A Tractable Inference Algorithm for Diagnosing Multiple Diseases
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
Qualtitative propagation and scenario-based scheme for exploiting probabilistic reasoning
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Representations and algorithms for efficient inference in bayesian networks
Representations and algorithms for efficient inference in bayesian networks
Exploiting causal independence in Bayesian network inference
Journal of Artificial Intelligence Research
A computational model for causal and diagnostic reasoning in inference systems
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Symbolic probabilistic inference in belief networks
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Inference with causal independence in the CPSC network
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Independence of causal influence and clique tree propagation
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Loop Corrections for Approximate Inference on Factor Graphs
The Journal of Machine Learning Research
Using Ranked Nodes to Model Qualitative Judgments in Bayesian Networks
IEEE Transactions on Knowledge and Data Engineering
Inference in the Promedas Medical Expert System
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Exploiting causal independence using weighted model counting
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Variable elimination for influence diagrams with super value nodes
International Journal of Approximate Reasoning
Assessing critical success factors for military decision support
Expert Systems with Applications: An International Journal
Exploiting structure in weighted model counting approaches to probabilistic inference
Journal of Artificial Intelligence Research
Real-time inference with large-scale temporal bayes nets
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Exploiting functional dependence in bayesian network inference
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Agent-Based parsimonious decision support paradigm employing bayesian belief networks
DAMAS'05 Proceedings of the 2005 international conference on Defence Applications of Multi-Agent Systems
An ontology-based approach for constructing Bayesian networks
Data & Knowledge Engineering
Probabilistic inference with noisy-threshold models based on a CP tensor decomposition
International Journal of Approximate Reasoning
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The noisy-or and its generalization noisy-max have been utilized to reduce the complexity of knowledge acquisition. In this paper, we present a new representation of noisy-max that allows for efficient inference in general Bayesian networks. Empirical studies show that our method is capable of computing queries in well-known large medical networks, QMR-DT and CPCS, for which no previous exact inference method has been shown to perform well.